Cognitive declines after deep brain stimulation are likely to be attributable to more than caudate penetration and lead location
Bibliographic record
Abstract
Sir, We have read the follow-up paper from the German multi-centre randomized deep brain stimulation (DBS) trial (Witt et al. , 2013) with great interest. The authors conducted a study investigating the relationship between DBS lead trajectory and cognitive decline after surgery performed in patients with Parkinson’s disease. They concluded that penetration of the caudate nucleus was a risk factor for global cognitive decline, and that suboptimal placement of the electrode outside of the subthalamic nucleus (STN) also increased the risk of verbal fluency decline. These were interesting findings, however, we strongly suspect that these two issues make up only a subset of what is likely multiple factors affecting DBS cognitive outcome. The pathophysiology of cognitive decline in Parkinson’s disease is complex, and cognitive decline after STN DBS may be affected by baseline cognitive dysfunction, brain atrophy, and by surgical complications (e.g. intracranial haemorrhage). To more closely examine this issue, …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".